Abstract
Knowledge-based organizations (KBOs) such as universities, research institutes, and research centers at businesses and industries manage their projects in pursuit of the goals of their organizations. It is well understood that collaboration becomes one of the most important factors for successful completion of these projects. In performing a project jointly, it is important for project team members to know who has the required knowledge. Thus it is imperative to assess what and how much the employees know. Using a knowledge-based social network and its basic approach, a new method is proposed to analyze the knowledge and collaboration collectively possessed by the employees of a KBO. This study first deal with the methodologies of evaluating knowledge and collaboration possessed both by individuals and the organization. Since the quantitative evaluation is essential in developing a series of evaluating methods, the measures of knowledge and collaboration are derived. Then, the knowledge network types of KBO and the network roles of KBO members are discussed. Four types of knowledge-based social network and four roles of network members are also discussed respectively. An evaluation fuzzy model is proposed to test the feasibility of the knowledge-based social network and its measures. A case study is used to demonstrate effectiveness of the proposed model.
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This work was supported by the 2008 Research Fund (No. 1.080008.01) of UNIST, Ulsan 689–798, Korea.
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Wi, H., Jung, M. (2014). An Evaluation Fuzzy Model and Its Application for Knowledge-Based Social Network. In: Pedrycz, W., Chen, SM. (eds) Social Networks: A Framework of Computational Intelligence. Studies in Computational Intelligence, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-02993-1_14
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DOI: https://doi.org/10.1007/978-3-319-02993-1_14
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